Magnetic Resonance (MR) images provide invaluable information to medical practitioners. However, due to the presence of imaging artifacts, anatomical variability, varying contrast properties, and poor registration, conventional techniques do not yield satisfactory results over a wide range of scan types and neuroanatomies without manual intervention. Moreover, traditional techniques are not robust enough for large scale analyses.
Thus, there is a need for an image processing technique that is robust and accurate.